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Dragonfly optimization and constraint measure-based load balancing in cloud computing

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Abstract

Load balancing is the significant task in the cloud computing because the cloud servers need to store avast amount of information which increases the load on the servers. The objective of the load balancing technique is that it maintains a trade-off on servers by distributing equal load with less power. Accordingly, this paper presents the load balancing technique based on the constraint measure. Initially, the capacity and load of each virtual machine are calculated. If the load of the virtual machine is greater than the balanced threshold value then,the load balancing algorithm is used for allocating the tasks. The load balancing algorithm calculates the deciding factor of each virtual machine and checks the load of the virtual machine. Then, it calculates the selection factor of each task. Then, the task which has better selection factor is allocated to the virtual machine. The performance of the proposed load balancing method is evaluated with the existing load balancing methods, such as HBB-LB, DLB, and HDLB for the evaluation metrics load and capacity. The experimental results show that the proposed method migrate only three tasks while the existing method HDLB migrates seven tasks.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Kakatiya Institute of Technology and Science, Warangal, Telangana, India

    Vijayakumar Polepally

  2. Department of Computer Science and Engineering, JNTUH College of Engineering, Manthani, Peddapalli, Telangana, India

    K. Shahu Chatrapati

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  1. Vijayakumar Polepally
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  2. K. Shahu Chatrapati
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Correspondence to Vijayakumar Polepally.

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Polepally, V., Shahu Chatrapati, K. Dragonfly optimization and constraint measure-based load balancing in cloud computing. Cluster Comput 22 (Suppl 1), 1099–1111 (2019). https://doi.org/10.1007/s10586-017-1056-4

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  • DOI: https://doi.org/10.1007/s10586-017-1056-4

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